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Non-classical transpeptidases yield insight into new antibacterials.

ABSTRACT: Bacterial survival requires an intact peptidoglycan layer, a three-dimensional exoskeleton that encapsulates the cytoplasmic membrane. Historically, the final steps of peptidoglycan synthesis are known to be carried out by D,D-transpeptidases, enzymes that are inhibited by the ?-lactams, which constitute >50% of all antibacterials in clinical use. Here, we show that the carbapenem subclass of ?-lactams are distinctly effective not only because they inhibit D,D-transpeptidases and are poor substrates for ?-lactamases, but primarily because they also inhibit non-classical transpeptidases, namely the L,D-transpeptidases, which generate the majority of linkages in the peptidoglycan of mycobacteria. We have characterized the molecular mechanisms responsible for inhibition of L,D-transpeptidases of Mycobacterium tuberculosis and a range of bacteria including ESKAPE pathogens, and used this information to design, synthesize and test simplified carbapenems with potent antibacterial activity.

SUBMITTER: Kumar P

PROVIDER: S-EPMC5477059 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

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Non-classical transpeptidases yield insight into new antibacterials.

Kumar Pankaj P Kumar Pankaj P Kaushik Amit A Lloyd Evan P EP Li Shao-Gang SG Mattoo Rohini R Ammerman Nicole C NC Bell Drew T DT Perryman Alexander L AL Zandi Trevor A TA Ekins Sean S Ginell Stephan L SL Townsend Craig A CA Freundlich Joel S JS Lamichhane Gyanu G

Nature chemical biology 20161107 1

Bacterial survival requires an intact peptidoglycan layer, a three-dimensional exoskeleton that encapsulates the cytoplasmic membrane. Historically, the final steps of peptidoglycan synthesis are known to be carried out by D,D-transpeptidases, enzymes that are inhibited by the β-lactams, which constitute >50% of all antibacterials in clinical use. Here, we show that the carbapenem subclass of β-lactams are distinctly effective not only because they inhibit D,D-transpeptidases and are poor substr ...[more]

PMID: 27820797

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Project description:Variety advancement decisions for root quality and yield-related traits in cassava are complex due to the variable patterns of genotype-by-environment interactions (GEI). Therefore, studies focused on the dissection of the existing patterns of GEI using linear-bilinear models such as Finlay-Wilkinson (FW), additive main effect and multiplicative interaction (AMMI), and genotype and genotype-by-environment (GGE) interaction models are critical in defining the target population of environments (TPEs) for future testing, selection, and advancement. This study assessed 36 elite cassava clones in 11 locations over three cropping seasons in the cassava breeding program of IITA based in Nigeria to quantify the GEI effects for root quality and yield-related traits. Genetic correlation coefficients and heritability estimates among environments found mostly intermediate to high values indicating high correlations with the major TPE. There was a differential clonal ranking among the environments indicating the existence of GEI as also revealed by the likelihood ratio test (LRT), which further confirmed the statistical model with the heterogeneity of error variances across the environments fit better. For all fitted models, we found the main effects of environment, genotype, and interaction significant for all observed traits except for dry matter content whose GEI sensitivity was marginally significant as found using the FW model. We identified TMS14F1297P0019 and TMEB419 as two topmost stable clones with a sensitivity values of 0.63 and 0.66 respectively using the FW model. However, GGE and AMMI stability value in conjunction with genotype selection index revealed that IITA-TMS-IBA000070 and TMS14F1036P0007 were the top-ranking clones combining both stability and yield performance measures. The AMMI-2 model clustered the testing environments into 6 mega-environments based on winning genotypes for fresh root yield. Alternatively, we identified 3 clusters of testing environments based on genotypic BLUPs derived from the random GEI component.

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Non-classical transpeptidases yield insight into new antibacterials.

Publications

Non-classical transpeptidases yield insight into new antibacterials.

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